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TNC is a non-linear optimizer. To use it, you must provide a function to minimize. The function must take one argument: the list of coordinates where to evaluate the function; and it must return either a tuple, whose first element is the value of the function, and whose second argument is the gradient of the function (as a list of values); or None, to abort the minimization.

TNC: A Python interface to the TNC non-linear optimizer

TNC: A Python interface to the TNC non-linear optimizer

TNC is a non-linear optimizer. To use it, you must provide a function to minimize. The function must take one argument: the list of coordinates where to evaluate the function; and it must return either a tuple, whose first element is the value of the function, and whose second argument is the gradient of the function (as a list of values); or None, to abort the minimization.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /scipy/optimize/_tnc.py#0
type: <class 'module'>
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